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A wearable surface-enhanced Raman scattering (SERS) sensor has been developed as a patch type to utilize as a molecular sweat sensor. Here, the SERS patch sensor is designed to comprise a sweat-absorbing layer, which is an interface to the human skin, an SERS active layer, and a dermal protecting layer that prevents damage and contaminations. A silk fibroin protein film (SFF) is a basement layer that absorbs aqueous solutions and filtrates molecules larger than the nanopores created in the β-sheet matrix of the SFF. On the SFF layer, a plasmonic silver nanowire (AgNW) layer is formed to enhance the Raman signal of the molecules that penetrated through the SERS patch in a label-free method. A transparent dermal protecting layer (DP) allows laser penetration to the AgNW layer enabling Raman measurement through the SERS patch without its detachment from the surface. The molecular detection capability and time-dependent absorption properties of the SERS patch are investigated, and then, the feasibility of its use as a wearable drug detection sweat sensor is demonstrated using 2-fluoro-methamphetamine (2-FMA) on the human cadaver skin. It is believed that the developed SERS patch can be utilized as various flexible and wearable biosensors for healthcare monitoring.

Surface-enhanced Raman scattering (SERS)-based assays have been recently developed to overcome the low detection sensitivity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SERS-based assays using magnetic beads in microtubes slightly improved the limit of detection (LoD) for SARS-CoV-2. However, the sensitivity and reproducibility of the method are still insufficient for reliable SARS-CoV-2 detection. In this study, we developed a SERS-based microdroplet sensor to dramatically improve the LoD and reproducibility of SARS-CoV-2 detection. Raman signals were measured for SERS nanotags in 140 droplets passing through a laser focal volume fixed at the center of the channel for 15 s. A comparison of the Raman signals of SERS nanotags measured in a microtube with those measured for multiple droplets in the microfluidic channel revealed that the LoD and coefficient of variation significantly improved from 36 to 0.22 PFU/mL and 21.2% to 1.79%, respectively. This improvement resulted from the ensemble average effects because the signals were measured for SERS nanotags in multiple droplets. Moreover, the total assay time decreased from 30 to 10 min. A clinical test was performed on patient samples to evaluate the clinical efficacy of the SERS-based microdroplet sensor. The assay results agreed well with those measured by the reverse transcription-polymerase chain reaction (RT-PCR) method. The proposed SERS-based microdroplet sensor is expected to be used as a new point-of-care diagnostic platform for quick and accurate detection of SARS-CoV-2 in the field.

In the last two decades, microfluidic technology has emerged as a highly efficient tool for the study of various chemical and biological reactions. Recently, we reported that high-throughput detection of various concentrations of a reagent is possible using a continuous gradient microfluidic channel combined with a surface-enhanced Raman scattering (SERS) detection platform. In this continuous flow regime, however, the deposition of nanoparticle aggregates on channel surfaces induces the "memory effect," affecting both sensitivity and reproducibility. To resolve this problem, a SERS-based gradient droplet system was developed. Herein, the serial dilution of a reagent was achieved in a stepwise manner using microfluidic concentration gradient generators. Then various concentrations of a reagent generated in different channels were simultaneously trapped into the tiny volume of droplets by injecting an oil mixture into the channel. Compared to the single-phase regime, this two-phase liquid/liquid segmented flow regime allows minimization of resident time distributions of reagents through localization of reagents in encapsulated droplets. Consequently, the sample stacking problem could be solved using this system because it greatly reduces the memory effect. We believe that this SERS-based gradient droplet system will be of significant utility in simultaneously monitoring chemical and biological reactions for various concentrations of a reagent.

This minireview reports the recent advances in surface-enhanced Raman scattering (SERS)-based assay devices for the diagnosis of infectious diseases. SERS-based detection methods have shown promise in overcoming the low sensitivity and multiplex detection problems inherent to fluorescence detection. Therefore, it is interesting to investigate the current status, challenges, and applications associated with SERS-based microdevices for the point-of-care (POC) diagnosis of infectious diseases. The majority of this review highlights three different types of microdevices, namely microfluidic channels, lateral flow assay strips, and three-dimensional nanostructured substrates. Furthermore, the integration of portable Raman spectrophotometry with microdevices provides an ideal platform for the diagnosis of various infectious diseases in the field. Integrated SERS-based assay systems also enable measurements in minimal sample volumes and at low analyte concentrations of viral or bacterial samples. A significant number of studies using the SERS-based assay system have been performed recently to realize POC diagnostics, especially under resource-limited conditions. This portable SERS sensor is expected to be a next-generation POC assay system that could overcome the limitations of current fluorescence-based assay systems. This minireview summarizes recent advances in the development of SERS-based microdevices for the diagnosis of infectious diseases. Lastly, challenges to overcome and future perspectives are discussed.

Surface-enhanced Raman scattering (SERS)-based aptasensors display high sensitivity for influenza A/H1N1 virus detection but improved signal reproducibility is required. Therefore, in this study, we fabricated a three-dimensional (3D) nano-popcorn plasmonic substrate using the surface energy difference between a perfluorodecanethiol (PFDT) spacer and the Au layer. This energy difference led to Au nanoparticle self-assembly; neighboring nanoparticles then created multiple hotspots on the substrate. The localized surface plasmon effects at the hot spots dramatically enhanced the incident field. Quantitative evaluation of A/H1N1 virus was achieved using the decrease of Raman peak intensity resulting from the release of Cy3-labeled aptamer DNAs from nano-popcorn substrate surfaces via the interaction between the aptamer DNA and A/H1N1 virus. The use of a Raman imaging technique involving the fast mapping of all pixel points enabled the reproducible quantification of A/H1N1 virus on nano-popcorn substrates. Average ensemble effects obtained by averaging all randomly distributed hot spots mapped on the substrate made it possible to reliably quantify target viruses. The SERS-based imaging aptasensor platform proposed in this work overcomes the issues inherent in conventional approaches (the time-consuming and labor-intensiveness of RT-PCR and low sensitivity and quantitative analysis limits of lateral flow assay kits). Our SERS-based assay for detecting A/H1N1 virus had an estimated limit of detection of 97 PFU mL−1 (approximately three orders of magnitude more sensitive than that determined by the enzyme-linked immunosorbent assay) and the approximate assay time was estimated to be 20 min. Thus, this approach provides an ultrasensitive, reliable platform for detecting viral pathogens.